Derive lidar grid metrics in raster format and model 2

Date: Aug 17, 2017

Software: FUSION

References:

FUSION Manual: http://forsys.cfr.washington.edu/fusion/FUSION_manual.pdf

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The lidar metrics I want to compute include Elev_mode, Elve_P95 and Total_retu.

1. Results got from FUSION

FUSION Results

2. Eliminate points with value -9999. This means these points are not covered by lidar data.

Eliminate -9999

3. Eliminate points with Elev_95 > 500 m. These points are located around the edges. Their heights are not properly corrected. Delete 231 out of 4865. Now have 4634 left for building lidar and Landsat model.

Elev_model > 500

Visualization in ArcMap

4. For overlapped points. There are overlaps between two adjacent lidar images. For the overlapped points, I chose the one with the larger total return. This is done in Python.

Ground-lidar model

1. Calculate lidar-biomass

Stepwise lidar-ground model:

STEPWISE selection model parameter estimates

LOG(BIOMASS)= -1.05151 + 0.99383*LOG(ELEV_MODE) + 0.32649*LOG(TOTAL_RETU) + 0.74666*LOG(ELEV_P95)

In Arcmap field calculator:

LOGAGB = -1.05151 + 0.32649*math.log10( !Total_retu! ) + 0.99383*math.log10( !Elev_mode! )+0.74666*math.log10( !Elev_P95! )

LIDARAGB = 10** !logAGB!

2. Comparison of ground biomass and lidar biomass.

Descriptive Statistics

Lidar - Landsat models

1. Landsat variables

Band 1-5, 7; RVI; DVI; NDVI; SAVI; MSAVI2

2. Building models

PROC REG DATA = Lidar_bio;

MODEL AGB_lidar =  RVI DVI NDVI SAVI MSAVI2 B1 B2 B3 B4 B5 B7 / SELECTION = RSQUARE;

RUN;

PROC REG DATA = Lidar_bio;

MODEL AGB_lidar =  RVI DVI NDVI SAVI MSAVI2 B1 B2 B3 B4 B5 B7 / SELECTION = STEPWISE;

RUN;

RSQUARE result:

RSQUARE result

Stepwise result:

STEPWISE Result

3. LOG transformation for just Y.

From results of STEPWISE, R square improves from 0.3059 to 0.3659.

Stepwise result for only log(Y)

4. Log both Xs and Y.

Log both Xs and Y

5. Comparison of R square for raw data, log transform Y, both log transform Xs and Y.

Underlined numbers are results from stepwise selection method.

I am going to use the model highlighted in green. It has 8 variables and has not much difference with the full model.

6. Lidar-Landsat model